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# Author: Simon Blanke |
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# Email: [email protected] |
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# License: MIT License |
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import time |
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import numpy as np |
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from multiprocessing import Pool |
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class Search: |
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def __init__(self, search_processes): |
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self.search_processes = search_processes |
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self.n_processes = len(search_processes) |
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self._n_process_range = range(0, self.n_processes) |
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print("self.n_processes", self.n_processes) |
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def run(self, max_time): |
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self.start_time = time.time() |
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self.results = {} |
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self.eval_times = {} |
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self.iter_times = {} |
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self.best_scores = {} |
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self.pos_list = {} |
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self.score_list = {} |
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if len(self.search_processes) == 1: |
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self._run_job(0) |
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else: |
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self._run_multiple_jobs() |
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return ( |
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self.results, |
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self.pos_list, |
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self.score_list, |
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self.eval_times, |
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self.iter_times, |
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self.best_scores, |
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) |
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def _search_multiprocessing(self): |
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"""Wrapper for the parallel search. Passes integer that corresponds to process number""" |
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pool = Pool(self.n_processes) |
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_p_list = zip(*pool.map(self._run, self._n_process_range)) |
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return _p_list |
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def _run_job(self, nth_process): |
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_p_ = self._run(nth_process) |
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# self._get_attributes(_p_) |
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def _get_attributes(self, _p_): |
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self.results[self.process.obj_func] = self.process._process_results() |
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self.eval_times[self.process.obj_func] = self.process.eval_time |
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self.iter_times[self.process.obj_func] = self.process.iter_times |
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self.best_scores[self.process.obj_func] = self.process.score_best |
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if isinstance(_p_, list): |
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self.pos_list[self.process.obj_func] = [np.array(p.pos_list) for p in _p_] |
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self.score_list[self.process.obj_func] = [ |
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np.array(p.score_list) for p in _p_ |
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] |
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else: |
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self.pos_list[self.process.obj_func] = [np.array(_p_.pos_list)] |
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self.score_list[self.process.obj_func] = [np.array(_p_.score_list)] |
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def _run_multiple_jobs(self): |
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_p_list = self._search_multiprocessing() |
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for _ in range(int(self.n_processes / 2) + 2): |
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print("\n") |
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""" |
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for self.process, _p_ in zip(self.processlist, _p_list): |
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self._get_attributes(_p_) |
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""" |
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def _run(self, nth_process): |
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process = self.search_processes[nth_process] |
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return process.search(nth_process) |
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""" |
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def _time_exceeded(self): |
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run_time = time.time() - self.start_time |
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return self.study_para.max_time and run_time > self.study_para.max_time |
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def _initialize_search(self, study_para, nth_process, _info_): |
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study_para._set_random_seed(nth_process) |
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self.process = SearchProcess(nth_process, study_para, _info_) |
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self._pbar_.init_p_bar(nth_process, self.study_para) |
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""" |
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SimonBlanke /
Hyperactive
